Environmental exposures to mixtures of toxic chemicals have potential interaction effects that may lead to hazard index values exceeding one. However, current regulation levels, such as tolerable daily intake (TDI), are mostly based on experimental studies conducted with a single chemical compound. In this study, we assessed the relationships between melamine and di-(2-ethylhexyl) phthalate (DEHP) exposure and their coexposure with the early renal injury markers N-acetyl -D-glucosaminidase (NAG), albumin/creatinine ratio (ACR), and microalbuminuria in 1236 pregnant women. Various generalized linear models with interaction terms and Bayesian kernel machine regression models were used for the (co-)exposure response associations. We derived the benchmark dose (BMD) and the corresponding one-sided 95% confidence bound BMDL based on the estimated (covariate-adjusted) average daily intake of melamine and DEHP metabolites measured in spot urine of the women collected during the third trimester. Given a benchmark response of 0.1, the BMDL level of melamine (DEHP) exposure on NAG (ACR, microalbuminuria) was 2.67 (11.20, 4.45) μg/kg_bw/day, and it decreased to as low as 1.46 (3.83, 2.73) μg/kg_bw/day when considering coexposure to DEHP (melamine) up to the 90th percentile. Both the exposure threshold levels of melamine and DEHP for early renal injuries in pregnant women were several-fold to one order lower than the current recommended TDIs by the WHO and the US FDA and EPA and were even lower considering coexposure. Because of concurrent exposures in real-world environments, more stringent regulation levels are recommended in susceptible populations, such as pregnant women, due to potential synergistic mixture effects.
Keywords: Average daily intake; Bayesian kernel machine regression; Bayesian model averaging; Markov chain Monte Carlo simulations.
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